Scheduling problems overall assume that it is possible to identify stable criteria definitions measuring the quality of alternatives. In real world problems however, this does not ...
We present a novel affective goal selection mechanism for decision-making in agents with limited computational resources (e.g., such as robots operating under real-time constraint...
We present an efficient "sparse sampling" technique for approximating Bayes optimal decision making in reinforcement learning, addressing the well known exploration vers...
Tao Wang, Daniel J. Lizotte, Michael H. Bowling, D...
Much research concerning Satisfiability Modulo Theories is devoted to the design of efficient SMT-solvers that integrate a SATsolver with T -satisfiability procedures. The rewrite-...
Let f : {0, 1}n {0, 1} be a boolean function. For 0 let D (f) be the minimum depth of a decision tree for f that makes an error for fraction of the inputs x {0, 1}n . We also ma...